POMDP MODEL AND ITS SOLUTION FOR SPOKEN DIALOGUE SYSTEM

It seems that no excellent model is available for the design of dialogue manager although many spoken dialogue systems have come into practical use in recent years. Using Markov decision process （MDP） is an emerging direction that regards the dialogue strategy selection as a stochastic optimization problem. But the MDP model can’t fully reflect the characteristics of a dialogue system because of the uncertainty in the dialogue state. Based on the partially observable MDP （POMDP）, a new model for a spoken dialogue system is proposed. It uses the concept of partially observable to handle the uncertainty. Due to the limitation of the exact algorithms, emphais is put on heuristic approximation algorithms and their applicability in the dialogue system POMDP. Two methods for grid point selection are proposed in grid based approximation algorithms.